Studying the evolution of digital artifacts with ‘big data’

The National Science Foundation (NSF) has awarded a three-year grant totaling nearly $900,000 to trace human behaviors through big data. This marks the fourth NSF-awarded grant in the last five years that an interdisciplinary team of Temple faculty members has received to study the evolution of digital artifacts using large-scale digital trace data. The collaboration joins researchers from the Fox School’s Management Information Systems Department and College of Science and Technology (CST).

“When humans interact with digital systems, we leave a trace. Every call we make, every website we visit, it’s stamped with time and space information,” said Dr. Youngjin Yoo, the Harry A. Cochran Professor of Management Information Systems at the Fox School, and the research grant’s primary investigator. “What we do is constantly changing, and the trace data can act as DNA. What we focus on through this research is the repeat behaviors in humans that can be captured through digital trace data.

“Using those evolutionary patterns, we believe we can predict future behaviors of individuals and organizations. For example, by detecting the changes of commute patterns of individuals, we can predict overall public-transit systems’ performance in the future. Similarly, we want to be able to predict the changes in individual behaviors based on environmental changes. 

Yoo said he and the grant’s co-principal investigators will study digitally enabled processes in complex digital systems, which “are like a living ecosystem, in that they constantly evolve,” he said. If patterns in the trace data represent what they call “behavioral genes,” Yoo said, alterations to those behavioral routines are “gene mutations.” Eventually, he said, the research team envisions developing software that will better predict the changes to those behavioral genes.

The benefits in doing so, according to Yoo, “are endless.” In a healthcare application, trace data could develop a pattern by which a patient sees a doctor or produce an average cost of care per patient. In an industry sense, such “gene mutations” could impact performance and cost.

“On the surface,” Yoo said, “all smart phones, for example, look the same. But everybody’s phone is different because of apps. It used to be that the product’s designer would make the product, and that was the end of the story. Now, it’s only the beginning. Millions of apps are downloaded. They’re changing constantly.

“Our argument is that, particularly in digital space, innovation never remains the same. It constantly changes and takes different forms.”

The research team includes: Yoo; Dr. Sunil Wattal, Associate Professor of Management Information Systems at the Fox School; Dr. Zoran Obradovic, Laura H. Carnell Professor of Data Analytics at CST; and Dr. Rob Kulathinal, Assistant Professor of Biology at the College of Science and Technology.

The NSF-awarded research grant runs through Jan. 31, 2018.

– Christopher A. VitoAdd New

Skip to toolbar